Despite decades of research and dozens of antibiotics, bacterial pathogens are again among the leading causes of death in the West due to the rapid evolution of antibiotic resistance. Plasmid acquisition is the leading cause of the spread of antibiotic resistance in bacteria. Yet, there is a fundamental gap in our understanding of how to robustly block plasmid acquisition, especially with the selective pressure that antibiotics provide. The long-term goal of this proposal is to develop the information that will allow new therapies and approaches to be designed that limit plasmid uptake, substantially extending the lifetime of last-line antibiotic drugs. Importantly, a natural blueprint for blocking plasmid acquisition appears to exist in approximately 50% of sequenced bacterial genomes. Known as Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), CRISPR is a genetic circuit that cleaves and destroys specific previously encountered plasmid and viral sequences, thus inhibiting viruses and plasmids from establishing their genetic material in CRISPR+ cells. CRISPR comes at a likely cost of reduced genomic plasticity for its bacterial hosts, who can no longer use plasmid acquisition to rapidly evolve. The specific goal of this proposal is thus to define the mechanisms and selective pressures allowing bacteria to maintain CRISPR despite its costs. This goal is significant because of CRISPR's ability to block the prime route of antibiotic resistance spread, plasmid acquisition. We hypothesize that CRISPR is preserved in bacterial populations because it provides sustained antiviral immunity. To test this hypothesis, an interdisciplinary computational and experimental study is proposed. First, a novel stochastic model will be designed to compete CRISPR+ and CRISPR- bacteria under varying viral pressure and periodic antibiotic treatment. The model will enable us to quantify potential parameter regimes in which antiviral immunity maintains CRISPR+ cells for extended periods of time despite the cost of being unable to acquire plasmids. Further, the model will pinpoint whether optimal treatment regimes exist in which reducing antibiotic dosages can improve patient outcomes by preserving CRISPR+ commensal reservoirs. The basic assumptions that CRISPR provides a fitness advantage against viruses and a fitness disadvantage against antibiotics will then be tested experimentally in Enterococcus, a leading cause of antibiotic resistant hospital infections. By experimentally assaying the anti-plasmid and anti-viral efficienc of CRISPR in an Enterococcus genome, I will definitively test whether selection for CRISPR's antiviral immunity can inhibit the emergence of deadly multi-drug resistant pathogens.